Credibility of design rainfall estimates for drainage infrastructures : extent of disregard in Nigeria and proposed framework for practice
Aiyelokun, Oluwatobi ; Pham, Quoc Bao ; Aiyelokun, Oluwafunbi ; Malik, Anurag ; Adarsh, S. ; Mohammadi, Babak LU
; Linh, Nguyen Thi Thuy
and Zakwan, Mohammad
(2021)
In Natural Hazards
109(2).
p.1557-1588
- Abstract
Rainfall intensity or depth estimates are vital input for hydrologic and hydraulic models used in designing drainage infrastructures. Unfortunately, these estimates are susceptible to different sources of uncertainties including climate change, which could have high implications on the cost and design of hydraulic structures. This study adopts a systematic literature review to ascertain the disregard of credibility assessment of rainfall estimates in Nigeria. Thereafter, a simple framework for informing the practice of reliability check of rainfall estimates was proposed using freely available open-source tools and applied to the north central region of Nigeria. The study revealed through a synthesis matrix that in the last decade, both... (More)
Rainfall intensity or depth estimates are vital input for hydrologic and hydraulic models used in designing drainage infrastructures. Unfortunately, these estimates are susceptible to different sources of uncertainties including climate change, which could have high implications on the cost and design of hydraulic structures. This study adopts a systematic literature review to ascertain the disregard of credibility assessment of rainfall estimates in Nigeria. Thereafter, a simple framework for informing the practice of reliability check of rainfall estimates was proposed using freely available open-source tools and applied to the north central region of Nigeria. The study revealed through a synthesis matrix that in the last decade, both empirical and theoretical methods have been applied in predicting design rainfall intensities or depths for different frequencies across Nigeria, but none of the selected studies assessed the credibility of the design estimates. This study has established through the application of the proposed framework that drainage infrastructure designed in the study area using 100–1000-year return periods are more susceptible to error. And that the extent of the credibility of quantitative estimates of extreme rains leading to flooding is not equal for each variability indicator across a large spatial region. Hence, to optimize informed decision-making regarding flood risk reduction by risk assessor, variability and uncertainty of rainfall estimates should be assessed spatially to minimize erroneous deductions.
(Less)
- author
- Aiyelokun, Oluwatobi
; Pham, Quoc Bao
; Aiyelokun, Oluwafunbi
; Malik, Anurag
; Adarsh, S.
; Mohammadi, Babak
LU
; Linh, Nguyen Thi Thuy
and Zakwan, Mohammad
- organization
- publishing date
- 2021-07-19
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Design rainfall estimates, Parametric bootstrap, Stochastic simulation, Two-dimensional Monte Carlo framework, Variability and uncertainty analysis
- in
- Natural Hazards
- volume
- 109
- issue
- 2
- pages
- 1557 - 1588
- publisher
- Springer
- external identifiers
-
- scopus:85110789908
- ISSN
- 0921-030X
- DOI
- 10.1007/s11069-021-04889-1
- language
- English
- LU publication?
- yes
- id
- 94715871-f78a-4fc9-8308-152f3a62e6cb
- date added to LUP
- 2021-08-02 09:43:09
- date last changed
- 2024-01-24 11:05:05
@article{94715871-f78a-4fc9-8308-152f3a62e6cb,
abstract = {{<p>Rainfall intensity or depth estimates are vital input for hydrologic and hydraulic models used in designing drainage infrastructures. Unfortunately, these estimates are susceptible to different sources of uncertainties including climate change, which could have high implications on the cost and design of hydraulic structures. This study adopts a systematic literature review to ascertain the disregard of credibility assessment of rainfall estimates in Nigeria. Thereafter, a simple framework for informing the practice of reliability check of rainfall estimates was proposed using freely available open-source tools and applied to the north central region of Nigeria. The study revealed through a synthesis matrix that in the last decade, both empirical and theoretical methods have been applied in predicting design rainfall intensities or depths for different frequencies across Nigeria, but none of the selected studies assessed the credibility of the design estimates. This study has established through the application of the proposed framework that drainage infrastructure designed in the study area using 100–1000-year return periods are more susceptible to error. And that the extent of the credibility of quantitative estimates of extreme rains leading to flooding is not equal for each variability indicator across a large spatial region. Hence, to optimize informed decision-making regarding flood risk reduction by risk assessor, variability and uncertainty of rainfall estimates should be assessed spatially to minimize erroneous deductions.</p>}},
author = {{Aiyelokun, Oluwatobi and Pham, Quoc Bao and Aiyelokun, Oluwafunbi and Malik, Anurag and Adarsh, S. and Mohammadi, Babak and Linh, Nguyen Thi Thuy and Zakwan, Mohammad}},
issn = {{0921-030X}},
keywords = {{Design rainfall estimates; Parametric bootstrap; Stochastic simulation; Two-dimensional Monte Carlo framework; Variability and uncertainty analysis}},
language = {{eng}},
month = {{07}},
number = {{2}},
pages = {{1557--1588}},
publisher = {{Springer}},
series = {{Natural Hazards}},
title = {{Credibility of design rainfall estimates for drainage infrastructures : extent of disregard in Nigeria and proposed framework for practice}},
url = {{http://dx.doi.org/10.1007/s11069-021-04889-1}},
doi = {{10.1007/s11069-021-04889-1}},
volume = {{109}},
year = {{2021}},
}